Image sensors have become ubiquitous. They are widely used in digital still cameras, cellular phones, security cameras, as well as, medical, automobile, and other applications. The technology used to manufacture image sensors, and in particular, complementary metal-oxide-semiconductor (CMOS) image sensors, has continued to advance at great pace. For example, as digital imaging becomes more prevalent, technology strives to achieve images and video having better resolution and color accuracy.
Conventional CMOS image sensors typically include an array of pixels, where each pixel includes a photodiode that transforms incident light into an electrical charge. Each individual pixel has an output that, for a fixed exposure time, eventually saturates with increasing light intensity. Saturation of the photodiodes can produce unwanted image smearing due to an effect known as blooming, where excess charge spreads into neighboring pixels. Thus, one aim of the image sensor is to achieve images in which objects are exposed properly, i.e., not too bright or too dark. Conventional image sensors often provide images whose exposures are not optimized. Some conventional image sensors may apply post image-acquisition algorithms to allow the digital image data to be further processed to achieve a particular color and intensity associated with a specific pixel. However, the more post image-acquisition corrections that are applied to an image, the more the overall quality of an image may degrade. A similar phenomenon is known to film photographers, who recognize that a better print may be made from a good negative than a print that is made after applying multiple, albeit advanced, manipulations to a mediocre negative.
In some conventional methods of automatic exposure control, a mean intensity of a single window of the whole or part of image is determined. The intensity may be luminance Y signal or one or more color channel signals. A predefined target mean intensity (i.e., a desired fixed mean intensity) is then assigned and the difference between the mean intensity and the target mean intensity is determined. Exposure correction is determined based upon this difference. However, using a single predefined target mean intensity may still result in too many bright and/or too many dark pixels present in the image, which can make the image uncomfortable to view. Furthermore, the application of a single window of part of image when calculating the mean intensity often results in less accurate target intensity estimation, since different parts of the image may have different intensity distributions.